PB2613: PREDICTIVE MODEL TO EVALUATE THE RISK OF IMMUNE THROMBOCYTOPENIA IN PATIENTS WITH SYSTEMIC LUPUS ERYTHEMATOSUS
Authors: Jesus Cornudella, Irene Carrion-Barbera, Sergio Vázquez Montes de Oca, Francesc Garcia-Pallarols, Tarek Carlos Salman-Monte, Blanca Sanchez-Gonzalez
Journal: HemaSphere (2023)

Topic: 32. Platelet disorders Background: Systemic lupus erythematosus (SLE) is an autoimmune disease with a wide range of manifestations, including immune thrombocytopenia (ITP). The presence of ITP has been described in 7-40% of SLE patients. Aims: To create a predictive model to identify those SLE patients at risk of developing ITP over the course of the disease in the SLE cohort of the Hospital del Mar. Methods: We conducted a retrospective case-control study in which 407 medical records of SLE patients were reviewed: 22 patients had developed ITP after the diagnosis of SLE (cases) and were randomly matched by sex and age consecutively with 2 SLE patients without ITP (controls), and the differences between groups were analyzed. The variables with the most disparate frequency of occurrence between cases and controls were selected. The model consists of a Random Forest executed on a cohort of 66 patients. The cohort was corrected to obtain a correct balance of classes between patients who develop ITP and those who do not. The model was trained with 70% of the cohort and tested with the remaining 30%. The scores obtained were calculated by the average of the results obtained after running the model 1000 times. Results: A higher frequency of occurrence of hemolytic anemia (18.18% vs 0%), low C4 (20% vs 9.76%) and low CH50 (20% vs 7.89%) was observed in the cases and more frequent occurrence of oral ulcers (9.09% vs 27.27%), arthritis (59.09 vs 77.27%) and Raynaud’s phenomenon (0% vs 16.28%) in the controls at the time of SLE diagnosis (Seetable 1). During the course of SLE, a higher frequency of positivity for anticardiolipin (38.09% vs 22.72%) and anti-β2-glycoprotein (42.86% vs 11.36%) was observed in cases. The obtained model presents a sensitivity of 87.53%, a positive predictive value (PPV) of 81.92%, a specificity of 80.50%, an area under the curve (AUC) of 83.92% and an accuracy of 83.68% (SeeFigure 1). Table 1. Patients characteristics - VARIABLES CASES (N=22) CONTROLS (N=44) P-VALUE Gender Male Female 4/22 (18.22%)18/22 (81.81%) 8/44 (11.76%)36/44 (81.81%) 1.00 Clinical and biochemical parameters at SLE diagnosis Photosensitivity 11/22 (50%) 28/44 (63.63%) 0.304 Oral ulcers 2/22 (9.09%) 12/44 (27.27%) 0.117 Arthritis 13/22 (59.09%) 34/44 (77.27%) 0.154 Proteinuria 5/22 (22.72%) 6/44 (13.63%) 0.485 Nephritis 4/22 (18.18%) 4/44 (9.09%) 0.425 Hemolytic anemia 4/22 (18.18%) 0/44 (0%) 0.01 Leukopenia 8/22 (36.36%) 13/43 (30.23%) 0.780 Raynaud’s phenomenon 0/22 (0%) 7/43 (16.28%) 0.085 Complement Low C3 Low C4 Low CH50 10/21 (47.62%)4/20 (20%)4/20 (20%) 10/41 (24.39%)4/41 (9.76%)3/38 (7.89%) 0.0870.4200.219 Clinical and immunological parameters along SLE course Antibodies Antinuclear antibody Anti-dsDNA Anti- Sm Anti Ro0 Anti-Ro52 Anti-Ro60 Anti La Anti-RNP DNA-Crithidia APS antibodies Anticardiolipin Anti-β2GP1 Lupic anticoagulant 22/22 (100%)13/22 (59.09%)1/21 (4.76%)7/21 (33.33%)7/21 (33.33%)8/21 (38.09%)5/21 (23.81%)4/21 (19.05%)6/21 (28.57%)8/21 (38.09%)9/21 (42.86%)5/21 (23.81%) 43/43 (100%)25/44 (56.81%)6/43 (13.95%)17/43 (39.53%)14/43 (32.56%)20/43 (46.51%)9/44 (20.46%)11/43 (25.58%)9/39 (23.08%)10/44 (22.72%)5/44 (11.36%)5/43 (11.63%) 1.001.000.4100.7851.000.5980.7570.7550.7570.2410.0080.275 Clinical APS 4/22 (18.18%) 3/42 (7.14%) 0.220 Other connective tissue disease 6/22 (27.27%) 15/44 (34.09%) 0.780 Summary/Conclusion: In this study we have created a predictive model capable of assessing the risk of developing ITP in SLE patients. By combining 8 variables, the model shows a great capacity of prediction. It correctly predicts 87.53% of the SLE patients who will suffer ITP with an accuracy of 83.68%. This model has an exploratory nature and more independent studies are needed to confirm the findings of this work. Keywords: Immune thrombocytopenia (ITP), Autoimmune disease